A number of PrPM techniques have been proposed in the past decade. These techniques can be organized into three groups based on how the intervention policy prescribes interventions to improve a business value [1]}. The first group focuses on control flow to recommend the next best action or activity to improve a pre-defined KPI [2]}, [3]}, [4]}. The second focuses on a resource view to guide resource allocation decisions [5]}, [6]}. Finally, the third focuses on triggering interventions to avoid or mitigate the effect of undesired outcomes and considers both control flow and resources perspectives [7]}, [8]}, [9]}, [10]}.
The proposal in this paper belongs to the third group; It seeks to learn policies for triggering runtime interventions to prevent undesired outcomes under limited resources.
